Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4562878 | Food Research International | 2009 | 6 Pages |
Abstract
Nonlinear sequential parameter estimation method based on Gauss minimization technique was used for developing a computer program capable of simultaneously estimating volumetric heat capacity and thermal conductivity using transient temperature measurements for a one-dimensional conduction food subjected to constant heat flux on one side and insulated on the other side. Monte Carlo simulation technique was used to validate and investigate the performance of the algorithm by generating simulated experimental data with random errors using typical known experimental thermal property data. Despite the variability in the initial guess of the parameters required by the algorithm no convergence problems were encountered. The accuracy of the parameters prediction depends on the level of the errors of the measured temperature. Positioning the measurement sensor closer to the heating surface resulted in accurate parameter estimation in shorter heating time minimizing the risk of long heating time and elevated surface temperature which may results in physical-chemical changes influencing the accuracy of the parameter estimation.
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Authors
Ibrahim O. Mohamed,